Markov Model-Based Energy Efficiency Spectrum Sensing in Cognitive Radio Sensor Networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jiao, Yan | - |
dc.contributor.author | Joe, Inwhee | - |
dc.date.accessioned | 2022-07-15T19:27:14Z | - |
dc.date.available | 2022-07-15T19:27:14Z | - |
dc.date.created | 2021-05-11 | - |
dc.date.issued | 2016-01 | - |
dc.identifier.issn | 2090-7141 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/155378 | - |
dc.description.abstract | Cognitive Radio Sensor Network (CRSN), incorporating cognitive radio capability in wireless sensor networks, is a new paradigm of the next-generation sensor network. Sensor nodes are usually battery powered and hence have strict energy constraints. As a result, energy efficiency is also a very critical problem in the CRSN. In this paper, we focus on energy consumption because of spectrum sensing. Furthermore, we present an adaptive spectrum sensing time interval strategy, in which SUs can adjust the next spectrum sensing time interval according to the current spectrum sensing results (namely, channel status). In order to find an optimal spectrum sensing time interval, we introduce the Markov model. Then, we establish a Markov model-based mathematical modeling for analyzing the relationship between spectrum sensing time interval and prior spectrum sensing results. Finally, numerical results demonstrate that the proposed strategy with dynamic adaptive spectrum sensing time interval exceeded listen before talk (LBT) strategy which is widely used for traditional wireless sensor networks. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | HINDAWI LTD | - |
dc.title | Markov Model-Based Energy Efficiency Spectrum Sensing in Cognitive Radio Sensor Networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Joe, Inwhee | - |
dc.identifier.doi | 10.1155/2016/7695278 | - |
dc.identifier.scopusid | 2-s2.0-84959287904 | - |
dc.identifier.bibliographicCitation | JOURNAL OF COMPUTER NETWORKS AND COMMUNICATIONS, v.2016, pp.1 - 8 | - |
dc.relation.isPartOf | JOURNAL OF COMPUTER NETWORKS AND COMMUNICATIONS | - |
dc.citation.title | JOURNAL OF COMPUTER NETWORKS AND COMMUNICATIONS | - |
dc.citation.volume | 2016 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 8 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | POWER ALLOCATION | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | TIME | - |
dc.subject.keywordPlus | ACCESS | - |
dc.identifier.url | https://www.hindawi.com/journals/jcnc/2016/7695278/ | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.